Devops and Cloud Engineer

Design, deploy and manage secure, scalable and highly available cloud infrastructure.

Build and improve cloud environments across development, staging and production.

Work with engineering teams to integrate cloud services into the software development lifecycle.

Improve platform reliability, scalability, performance and maintainability.

Establish reusable and standardised platform capabilities that can be adopted across products.

Build tools and platform capabilities that help developers move faster and work more efficiently.

Develop self-service infrastructure patterns, reusable templates and standardised deployment practices.

Reduce manual operational work through automation and platform standards.

Partner with Engineering Managers, Solution Architects, Delivery teams and the DevOps leadership team to improve engineering flow and operational readiness.

Develop and maintain Infrastructure as Code using tools such as Terraform, Bicep, Ansible, CloudFormation or equivalent.

Build and maintain CI/CD pipelines to streamline software delivery.

Automate infrastructure provisioning, deployments, monitoring and operational processes.

Integrate cloud infrastructure, repositories, pipelines, secrets management and deployment workflows.

Implement and improve monitoring, logging, alerting and observability across cloud platforms and services.

Create visibility into system health, infrastructure usage, deployment performance and operational risks.

Support incident investigation, root cause analysis and reliability improvements.

Develop operational dashboards and metrics to help teams proactively identify issues.

Implement security controls across cloud infrastructure, including IAM, encryption, network security and secrets management.

Establish secure access models for users, services, pipelines and AI agents.

Work with Security and IT teams to ensure cloud platforms meet company security and governance standards.

Support access reviews, security assessments and remediation activities.

Help build the technical foundations required for AI-assisted and Agentic AI workflows.

Support the implementation of identity, access, observability and execution controls for AI agents.

Work with Architecture, Security and Engineering teams to establish safe and scalable operating patterns for AI agents.

Help develop practical guardrails covering access boundaries, data handling, auditability and operational accountability.

Explore and support emerging AI engineering technologies and platforms.

Monitor cloud usage and identify opportunities to improve cost efficiency and resource utilisation.

Support FinOps practices, resource tagging and cloud cost visibility.

Identify performance bottlenecks and infrastructure risks.

Support capacity planning and recommend improvements to scalability, reliability and cost efficiency.

Proven experience designing, deploying and managing production cloud infrastructure.

Strong hands-on experience with at least one major cloud platform, preferably Microsoft Azure and/or AWS.

Strong experience with Infrastructure as Code, such as Terraform, Bicep, Ansible, CloudFormation or similar.

Hands-on experience with CI/CD pipelines and modern software deployment practices.

Good understanding of cloud networking, including VNET/VPC, DNS, VPN, load balancing, firewalls, private endpoints and network security.

Experience implementing monitoring, logging, alerting and observability.

Strong scripting and automation skills using Python, Bash, PowerShell or similar.

Experience improving developer experience through self-service infrastructure, reusable templates and automation.

Strong understanding of cloud security, identity and access management.

Strong problem-solving skills and a proactive approach to improving systems and processes.

Good professional English communication skills.

Experience with FinOps, cloud cost optimisation and resource tagging.

Experience with Kubernetes, containers or container orchestration.

Experience with GitHub Actions or similar CI/CD platforms.

Experience supporting AI/Agentic AI engineering workflows.

Exposure to technologies such as LangChain, Sema
ntic Kernel or similar AI engineering ecosystems.

Experience working with AI tools such as Claude, ChatGPT or GitHub Copilot.

Experience working in a global or multi-market technology organisation.

Experience establishing platform standards, engineering guardrails or developer self-service capabilities.